ACQUISITION AND PROCESSING OF HIGH RESOLUTION HYPERSPECTRAL IMAGERIES FOR 3D MAPPING OF URBAN HEAT ISLANDS AND MICROPARTICLES OF MONTRÉAL

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1 ACQUISITION AND PROCESSING OF HIGH RESOLUTION HYPERSPECTRAL IMAGERIES FOR 3D MAPPING OF URBAN HEAT ISLANDS AND MICROPARTICLES OF MONTRÉAL Montreal - artistic representation (1784) years after its fundation Montreal - virtual representation (2017) years after its fundation Richard Mongeau q.l.s, M.Sc. (geodesy) Prof. Yves Baudouin Prof. François Cavayas

2 GLOBAL WARMING AND AIR POLLUTION STUDIES Regional scale satellite resolution Diurnal urban heat island blend of roofs, gardens and parking lots Prof. Yves Baudouin (2005, 2008, 2010, 2011) PM 2,5 interpolation permanent stations registred pollution gaz & PM Prof. François Cavayas

3 FRAMEWORK: «OBSERVATOIRE SPATIAL URBAIN» Urban scale airborne resolution (2012, 2016) Surface temperatures Day/Night AOD PM 2,5 2D/3D MAPPING AND ANALYSIS Surface temperatures and fine particles PHYSICAL PROPERTIES OF SURFACE COVER MATERIALS DATA BASE PREVISIONNAL MODELISATION

4 ACQUISITION OF HIGH RESOLUTION HYPERSPECTRAL IMAGERIES Summer 2016 Island of Montreal (500 km²) 1) Day and night, TASI camera imageries, respectively 2 m resolution (AIRPORT CONTRAINT) and 1 m resolution, solar and thermal spectrum (8,0-11,5 µm), 32 bands 2) Day, CAS I-1500 camera imageries 1 m resolution, near UV, visible, near-infrared (0,37-1,04 µnm), 96 bands Airborne survey by IItres Research Ltd

5 FIELD CONTROLS Geometric targets, air pollution stations, surface and air temperature sensors 22 air temperature sensors «HOBO» 11 materials or painted targets 53 municipal pools 15 monitoring stations PM 2,5 H= 3m 30 ground thermal sensors «ibutton»

6 GEOMETRIC CORRECTIONS OF IMAGERIES True orthophotos TASI IMAGERY Data after radiometric corrected submitted to geocorrection processing DIGITAL SURFACE MODEL (LiDAR) nov.- dec.2015, footprint > 25 cm, density: 10 pts/m², accuracy : ± 15 à 20 cm TASI IMAGERIES DAY resolution : 2 m RMS : ± 2,3 m NIGHT resolution : 1 m RMS: ± 1,5 m Validation with pools measurements solar,thermal (32 bands) CASI IMAGERY near UV, visible, near-infrared (96 bands) CASI IMAGERIES DAY resolution : 1 m RMS : ± 1,7 m Validation with TYVEK and pools measurements

7 ATMOSPHERIC CORRECTIONS OF THERMAL IMAGERIES TASI MODTRAN (ONTAR-PcModeWIN) temperature relative humidity barometric pression Lsensor = Latm + Lsurface τ Diff. Abs. Island of Montreal: 500 km² Refr. Day : 2m resolution Night: 1m resolution 32 bands for each pixel image temperature relative humidity barometric pression script with central wavelengths and spectral sensitivities for each TASi band meteorological data by flight line (airplane-ground) MODTRAN Code band by band atmospheric transmittance τ atmospheric path luminance Latm sky luminance Lsky

8 GROUND TEMPERATURE FROM TASI IMAGERIES Temperature Emissivity Separation algorithm atmospheric transmittance τ atmospheric path luminance Latm sky luminance Lsky Lsurface = (Lsensor - Latm) /τ Diff. Lsurface = ε L(Ts)+ ρlsky(tair) Abs. 1-ε=ρ Refr. Iterations band by band (λ,k1,k2) start ε=0,99 32 bands = 32 emissivities = 32 temperatures Ts = k2 / ln(k1/l + 1) 273 where L = (2h c2/λ5). (1/ehc/(λkT)-1) find εmax and Tmax σt = ±2 ºC estmated temperatures vs surface thermal controls 32 bands 32 emissivities 32 temperatures 1 temperature Day/Night TES Algorithm iteration 32 emissivties thermal inertia

9 3D MODEL OF SURFACE TEMPERATURES TEMPERATURE ANALYSIS analysis by pixel, material (asphalt, grass, concrete, metal ), object (street, sidewalk, artificial turf playground, parking lots, white and green roof ) TEMPERATURE ANALYSIS analysis by land use/covery (water, parks, residential, commercial, industrial ) T C increase with housing density parks, reference for intra heat islands during Day +5 C, +10 C still warm at night: main street, artificial turf field, building facade

10 SHADOWS ANALYSIS Shadow building simulation 20 august :00 Temperature surface at night 3:00 AM Temperature surface during day 12:00

11 HEAT ISLANDS USES Urban planning Trees planting Civil security

12 CANOPY HEAT ISLANDS STUDIES AIR SENSORS INTERPOLATION AIR TEMPERATURE EXTRAPOLATION Correlation 50 % (Day 10m Night 80m) GROUND SURFACE TEMPERATURE

13 SURFACE MATERIAL FROM CASI IMAGERIES Lsensor = Latm + Lsurface τ Diff. Abs. Refr. 96 bands CASI-150 imageries, 1 m resolution, near UV, visible, near-infrared (0,37-1,04 µnm) Material SPECTRAL ANALYSIS Ground (asphalt, concrete, grass, paver) Roof (asphalt, gravel, metal ) Permeability

14 AIR POLLUTION FROM CASI IMAGERIES Recovery of AOD Anthropogenic sources industrial emission, transportation chimney fire Lsensor = + Latm,+ Lsurface τ Lgas Code 6s and Laero Mixed layer Estimate Aerosol Optical Depth (AOD) on specific objects Dark targets (NVDI) Atmospheric radiance Latm isolate on dark targets ATMOSPH Code 6S Calculate Lgas Recover AOD

15 AIR POLLUTION FROM CASI IMAGERIES Estimation of fine particle PM2,5 from AOD AOD measurement in dark tagets area (hign density vegetation) Reference stations Interpolation/correlation auxiliary data PM2,5 estimation

16 «OBSERVATOIRE SPATIAL URBAIN» 3D GIS Ground surface cover surface temperature day/night emissivity albedo vegetation NVDI material (asphalt, concrete, grass, pavers ) permeabilty shadow of building or tree AOD/PM2,5 id cadastre ground area m² land use/covery: agriculture, park, residential (1, 2-5, +10), commercial, industrial, street and alley, public utilitie

17 «OBSERVATOIRE SPATIAL URBAIN» 3D GIS Roofs surface cover surface temperature day/night emissivity albedo vegetation NVDI material (asphalt, gravel, metal ) permeabilty shadows of buildings id adress building height slope/flat slope/flat roof roof area m² housing density Identify and study particurly green and white roofs

18 «OBSERVATOIRE SPATIAL URBAIN» DATA BASE TEMPERATURES FINE PARTICLES/ DARK TARGETS PHYSICAL PROPERTIES OF SURFACE COVER MATERIALS PREVISIONNAL MODELISATION

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